Sociocultural and cognitive influences of pain expression and assessment

Background: Health inequities in pain are rampant in the United States. Historically marginalized populations (HMPs) experience increased levels of pain, pain more often, and receive less pain treatment. Health inequities are largely based on verbal reports, suggesting providers are not standardized in their assessments of verbal pain. As pain is a complex phenomenon, it is important to understand the decision-making process underlying verbal self-report and to identify potential ways nonverbal information might impact both a person’s real and expected pain outcomes and how perceivers assess pain in another individual. Aim: Across four studies, we aimed to assess how individuals experience and report pain and how individuals perceive pain in others. We aimed to identify 1) how provider’s facial characteristics might impact a persons expected pain outcomes and 2) whether individuals varied in their confidence in their verbal self-reports of pain. We also aimed to 3) identify if individuals bias their pain assessment outcomes by sociocultural effects when presented computer-generated images of pain-related expressions and 4) when presented videos of real acute pain. Methods: We used several experimental methodologies and tools to assess pain experience and pain assessment. We used an experimental paradigm of acute heat pain to assess verbal self-reports of real acute pain and participant’s confidence in their pain reports. We used online methods, by presenting facial images and asking for perceiver self-reports, to assess how individuals’ perceptions of potential providers impact expected pain outcomes and how individuals perceive pain in computer-generated images. Online methods allowed us to reach a more general sample, across the United States and to safely collect data during the COVID- 19 pandemic. Finally, we used a mixed-methods approach, by running online sessions with telehealth visits to interact with each of our online participants. We investigated how individuals assess videos of acute heat pain and this mixed-methods approach allowed us to: collect more information from each participant, reinforce the instructions and verify task understanding, and to continue safe data collection during the COVID-19 pandemic. Results: Individuals exhibited influences in their expected pain and medication outcomes in an online task in which participants were presented several potential providers. Participants expected less pain and medication use when viewing similar providers. However, the effect of perceived similarity was stronger for White compared to other racialized participants. Individuals also reported high levels of confidence in their verbal self-reports of pain during an in-person pain calibration task with aversive heat stimulation. Although reports of confidence were high, we did observe significant variability in explicit reports of confidence that associated with pain rating reaction time. We also observed biases in our participants when they assessed pain in others. Although we did not observe sociocultural biases in pain assessment to computer-generated images, we did observe biases in pain perception compared to other emotions. Pain was rarely perceived (7%) when it was equally presented compared to other basic emotions. We also observed biases by race and gender in emotionrelated decisions. Finally, when we presented participants with videos of acute heat pain, as opposed to stills of computer-generated images, perceivers exhibited typical biases by target race. Perceivers were less accurate, saw pain less often, and reported less intense pain in Black targets compared to White targets. Racial biases pain categorizations were increased by perceived similarity and racial biases in pain intensity judgments were increased with greater endorsement in explicit racism via the Modern Racism Scale. Finally, we observed atypical gender biases, such that perceivers reported pain more often and more intense pain in women targets compared to men. Conclusions: Individuals are biased in their expected pain outcomes based on the facial traits of potential providers, suggesting a need to diversify the medical workforce and the potential importance for patient input in selecting their providers. Individuals also typically report pain ratings with high levels of confidence; however, variability does exist and suggests confidence is another measure of verbal report that can be probed by researchers and providers alike. Finally, our results suggest that individuals can have difficulty identifying pain in pain-related expressions without priming or context. However, using more ecologically valid stimuli (i.e., the videos of real acute pain that we created), allowed us to experimentally extend pain assessment biases by race to experimental settings and indicate racial bias as a potential target for pain assessment bias intervention